To make sure that the condition is not ignored by the generator, we insert the condition information into both the generator and the discriminator following the practice in [1]}. First, we insert one Class Batch Normalization (CBN) layer into each layer of the generator. Second, we use a projection layer to project the class embedding into the discriminator output. The right part of Figure REF  shows the discriminator details. First, the label is processed by an embedding layer to obtain its class embedding \(e\) . Then, we apply an inner product between \(e\)  and the extracted feature \(D_{\phi _1(\mathbf {x})}\) . Later, the two branches are added together to produce the output result.
